TrafficGenius aims to minimize traffic congestion in areas where drivers pass through multiple traffic signals to travel from one location to another. TrafficGenius utilizes a unique algorithm relying on artificial intelligence to streamline traffic patterns, thereby allowing continuing refinements to the algorithm as the TrafficGenius tool is implemented in subsequent towns and cities.
The algorithm is in development to use publicly available data, to build a foundation from which arterial traffic patterns can be improved. These data sources must be expertly combined, computed, and transformed to realize the full potential of the TrafficGenius Suite. To set this tool apart from similar traffic optimization tools, this algorithm utilizes reinforcement learning, a branch of artificial intelligence within the machine learning arena. As the TrafficGenius tool is applied around the nation, the artificial intelligence will create additional enhancements to the algorithm to produce high-level results.
Scott Murdoch
TrafficGenius is the brainchild of Scott Murdoch, data scientist director and specialist in enterprise-class big data analytics. With a Ph.D. in economics and extensive background in artificial intelligence, Scott blends both skillsets to effectively research, develop, and manage all aspects of TrafficGenius.
Frederick Schwartz
